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Protposer: The web server that readily proposes protein stabilizing mutations with high PPV
Protein stability is a requisite for most biotechnological and medical applications of proteins. As natural proteins tend to suffer from a low conformational stability ex vivo, great efforts have been devoted toward increasing their stability through rational design and engineering of appropriate mu...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Research Network of Computational and Structural Biotechnology
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9133766/ https://www.ncbi.nlm.nih.gov/pubmed/35664235 http://dx.doi.org/10.1016/j.csbj.2022.05.008 |
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author | García-Cebollada, Helena López, Alfonso Sancho, Javier |
author_facet | García-Cebollada, Helena López, Alfonso Sancho, Javier |
author_sort | García-Cebollada, Helena |
collection | PubMed |
description | Protein stability is a requisite for most biotechnological and medical applications of proteins. As natural proteins tend to suffer from a low conformational stability ex vivo, great efforts have been devoted toward increasing their stability through rational design and engineering of appropriate mutations. Unfortunately, even the best currently used predictors fail to compute the stability of protein variants with sufficient accuracy and their usefulness as tools to guide the rational stabilisation of proteins is limited. We present here Protposer, a protein stabilising tool based on a different approach. Instead of quantifying changes in stability, Protposer uses structure- and sequence-based screening modules to nominate candidate mutations for subsequent evaluation by a logistic regression model, carefully trained to avoid overfitting. Thus, Protposer analyses PDB files in search for stabilization opportunities and provides a ranked list of promising mutations with their estimated success rates (eSR), their probabilities of being stabilising by at least 0.5 kcal/mol. The agreement between eSRs and actual positive predictive values (PPV) on external datasets of mutations is excellent. When Protposer is used with its Optimal kappa selection threshold, its PPV is above 0.7. Even with less stringent thresholds, Protposer largely outperforms FoldX, Rosetta and PoPMusiC. Indicating the PDB file of the protein suffices to obtain a ranked list of mutations, their eSRs and hints on the likely source of the stabilization expected. Protposer is a distinct, straightforward and highly successful tool to design protein stabilising mutations, and it is freely available for academic use at http://webapps.bifi.es/the-protposer. |
format | Online Article Text |
id | pubmed-9133766 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Research Network of Computational and Structural Biotechnology |
record_format | MEDLINE/PubMed |
spelling | pubmed-91337662022-06-04 Protposer: The web server that readily proposes protein stabilizing mutations with high PPV García-Cebollada, Helena López, Alfonso Sancho, Javier Comput Struct Biotechnol J Research Article Protein stability is a requisite for most biotechnological and medical applications of proteins. As natural proteins tend to suffer from a low conformational stability ex vivo, great efforts have been devoted toward increasing their stability through rational design and engineering of appropriate mutations. Unfortunately, even the best currently used predictors fail to compute the stability of protein variants with sufficient accuracy and their usefulness as tools to guide the rational stabilisation of proteins is limited. We present here Protposer, a protein stabilising tool based on a different approach. Instead of quantifying changes in stability, Protposer uses structure- and sequence-based screening modules to nominate candidate mutations for subsequent evaluation by a logistic regression model, carefully trained to avoid overfitting. Thus, Protposer analyses PDB files in search for stabilization opportunities and provides a ranked list of promising mutations with their estimated success rates (eSR), their probabilities of being stabilising by at least 0.5 kcal/mol. The agreement between eSRs and actual positive predictive values (PPV) on external datasets of mutations is excellent. When Protposer is used with its Optimal kappa selection threshold, its PPV is above 0.7. Even with less stringent thresholds, Protposer largely outperforms FoldX, Rosetta and PoPMusiC. Indicating the PDB file of the protein suffices to obtain a ranked list of mutations, their eSRs and hints on the likely source of the stabilization expected. Protposer is a distinct, straightforward and highly successful tool to design protein stabilising mutations, and it is freely available for academic use at http://webapps.bifi.es/the-protposer. Research Network of Computational and Structural Biotechnology 2022-05-10 /pmc/articles/PMC9133766/ /pubmed/35664235 http://dx.doi.org/10.1016/j.csbj.2022.05.008 Text en © 2022 The Authors https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Research Article García-Cebollada, Helena López, Alfonso Sancho, Javier Protposer: The web server that readily proposes protein stabilizing mutations with high PPV |
title | Protposer: The web server that readily proposes protein stabilizing mutations with high PPV |
title_full | Protposer: The web server that readily proposes protein stabilizing mutations with high PPV |
title_fullStr | Protposer: The web server that readily proposes protein stabilizing mutations with high PPV |
title_full_unstemmed | Protposer: The web server that readily proposes protein stabilizing mutations with high PPV |
title_short | Protposer: The web server that readily proposes protein stabilizing mutations with high PPV |
title_sort | protposer: the web server that readily proposes protein stabilizing mutations with high ppv |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9133766/ https://www.ncbi.nlm.nih.gov/pubmed/35664235 http://dx.doi.org/10.1016/j.csbj.2022.05.008 |
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